Copper Price Forecasting (2013 Update)

In a 2012 post we looked at the copper price forecasts of Cochilco since 2005. To do so we looked at the "Informe Trmestral del Mercado de Cobre" which is published on a quarterly basis.

The following graph shows the development of the forecasted copper price (or rather the deviation from the ex-post price) as a function of the number of days before the end of the period for which the forecast was made.

Separately we show an update of the graph we already showed in last year´s post comparing the deviation of the forecasted price made 18 months before the end of the forecasted period with the spot price at the forecasting date.

2012 was a relatively good year with a relatively small forecasting error, undoubtedely assited by relatively low volatility of copper price and the absence of large price movements

Metal and Ore Exports (as a percentage of exports) 1988 to 2010

The Worldbank has nifty page allowing to plot numerous trade related data points:

The World Integrated Trade Solution (WITS) is a software developed by the world Bank, in close collaboration and consultation with various International Organizations including United Nations Conference on Trade and Development (UNCTAD), International Trade Center (ITC), United Nations Statistical Division (UNSD) and World Trade Organization (WTO). WITS gives you access to major international trade, tariffs and non-tariff data compilations:

• The UN COMTRADE database maintained by the UNSD: Exports and imports by detailed commodity and partner country
• The TRAINS maintained by the UNCTAD: Imports, Tariffs, Para-Tariffs & Non-Tariff Measures at national tariff level
• The IDB and CTS databases maintained by the WTO: MFN Applied, Preferential & Bound Tariffs at national tariff level

WITS is a data consultation and extraction software with simulation capabilities. WITS is a free software. However, access to databases themselves can be fee-charging or limited depending on your status. WITS is a system that is still evolving and we will be adding more features. In subsequent releases of WITS we plan to provide additional features including coupling with ITC's MACMAP system.

We used WITS to plot the share of metals and ore exports as a percentage of total exports for the ten largest copper exporters. Zambia followed by Chile and Peru lead this metric through the whole period (1988 to 2010).

Copper, Gold and Silver Price Changes after Quantitative Easing Announcements

Following a post of ZeroHedge ("Spot the Odd One Out") we were curious to see how copper price reacted to the various QE announcements in the last couple of years. The complement the picture we also looked at gold and silver.

Price data we have downlaoded from Wikiposit (front contracts): Copper, Gold and Silver.

According to our count we have five FOMC announcement with QE characteristics:

1. November 25, 2008
2. March 18, 2009
3. November 3, 2010
4. September 13, 2012
5. December 12, 2012

In order to capture the entire price change due to the announcement we have looking at the closing prices at the day before the announcement (t-1) and after the announcement (t+1) and obtained the following results:

Data is here.

Copper Inventories with Producers

For the last two years the off-exchange copper inventory in China has been an important item when evaluating the copper market. While the anecdotal evidence has been strong, it has proven extremely difficult to come up with meaningful hard data. Nevertheless, a number of blogs particularly FT Alphaville have provided significant insight:

• China’s literally ground-breaking copper inventories (August 14, 2012)
• China is being buried alive in copper (April 26, 2012)
• Let’s count the copper with dust on it (May 31, 2011)
• China’s bonded-warehouse copper mystery (December 21, 2010)

We would like to add one additional piece to the puzzle by looking at producers inventory, particularly Codelco, the largest copper producer worldwide. While Codelco is not a publicly listed company, commendably it makes its quarterly reports reports available in the public domain.

We went through the the financial reports and focused on two metrics: inventory and revenues. We understand that inventory is broader than finished products. Nevertheless the ratio between inventory and revenues (inventory expressed in months of production) is very revealing:

The last data point is for the quarter ending on September 30, 2012. We view it to be quite interesting that the two previous episodes with the inventory exceeding 2 months of production were (i) in 2003 with copper prices below USD 2'000 per ton and (ii) in early 2009 with copper prices falling below USD 4'000. At the moment the (relatively) high inventory levels have not resulted in any price reaction.

We would also like to point out to some interesting movement in copper data as jsut published in the FT (Chinese copper data’s warning signal).

Chinese copper data have just taken a worrying turn for the worse. The country’s imports of the red metal tumbled 22 per cent in October to their lowest in more than a year. At the same time, stocks of the metal have risen to a record high: in October alone, inventories at Shanghai exchange and bonded warehouses collectively rose by about 135,000 tonnes, and are now not far off 1m tonnes, most traders believe. Put those two facts together, and the Chinese copper market appears to be flashing a warning signal. Indeed, back-of-the-envelope calculations suggest a month-on-month drop of almost 20 per cent in Chinese apparent copper demand in October.

Relationship between Cooper Price Change and S&P 500 Total Return

Today we would like to address whether any relationship between copper price and stock market returns can be observed. Both are often interpreted as leading indicators of economic health.

For the cooper price data, we have relied as usual on the USGS data (which we expanded back to 1850 also from USGS). For the S&P 500 data we have used Robert Shiller's data (Yale) going back to 1871. For the calculation of total return we took the dividends plus index valuation for any annual period.

Overall the picture is rather disappointing in the sense that there is really no dependency structure between the two variables as can also be seen in the graphic below:

A left tail dependency might be suspected visually (especially the 1931 data point with -37% copper price change and -40% S&P 500 total return), but corresponding statistical tests don't confirm such relationship.

Obviously the hypothesis of the high co-dependency between copper price changers and stock market return dates back to the Great Depression, where there correlation for the time period 1925 to 1935 was 65%.

However, in the recent episode surrounding the Great Recession, this co-dependency was much lower with a correlation coefficient of 31%.

In a future post we will look at monthly time series to better evaluate lagging behavior (for above episodes, it seems that S&P 500 was somehow leading copper price).